A quasi-likelihood approach for overdispersed binomial data when N isunobserved

摘要

Several methods for the analysis of binomial data when the denominator, N, is unknown have been developed. Each of these methods requires that the mean of the distribution of N is known. Ln this article, we develop a quasi-likelihood technique that allows for the estimation of the means of the distributions needed to define the expected value and variance of the observed response and suggest a different form of the variance function. We illustrate the results of the proposed analysis and the results obtained when the mean of the distribution of N is assumed known through the analysis of a surviving jejunal crypt data set. Although the proposed method shows inflated standard errors of the parameter estimates in the cited example, the proposed method performs as well as a previously published method in all simulated conditions. Moreover, in cases where E(N) is misspecified, the proposed method outperforms the previously published method.